Segregation in Motion: Dynamic and Static Views of Segregation among Recent Movers. Victoria Pevarnik. John Hipp

Segregation in Motion: Dynamic and Static Views of Segregation among Recent Movers Victoria Pevarnik John Hipp March 31, 2012

SEGREGATION IN MOTION 1 ABSTRACT This study utilizes a novel approach to study how immigration changes over time. Rather than computing segregation measures based on the existing population, we compute segregation measures among different categories of recent movers (those moving within the last 5 years from when the data was taken). We therefore are able to assess segregation among recent movers across the U.S. using the index of dissimilarity. Measuring segregation among different ethnic recent movers groups produces results that capture segregation in motion, or in other words, changes in segregation as they occur. Findings reveal that domestic movers are almost always less segregated than the static population, that moving from farther distances almost always results in higher rates of segregation, and foreign movers are more segregated than other mover groups without exception.

SEGREGATION IN MOTION 2 Segregation in Motion: Dynamic and Static Views of Segregation among Recent Movers Residential ethnic segregation has negative social implications for ethnic minority groups in America (Charles 2003). Segregation patterns and trends are traditionally considered to be changing through residential mobility (Maloutas 2004: 195). One measure of segregation, the index of dissimilarity (D), assesses the evenness of the population of two groups in one area, usually a county (Massey 1988). The dissimilarity index can be used to measure segregation rates in cross sectional studies across two ethnic groups at one time or to calculate these rates at two times, comparing them to derive changes in rates of segregation. This study utilizes a novel approach to study how immigration changes over time. Rather than computing segregation measures based on the existing population, we compute segregation measures among different categories of recent movers (those moving within the last 5 years). We therefore are able to assess segregation among recent movers across the U.S. using the index of dissimilarity. Measuring segregation among different ethnic recent movers groups produces results that capture segregation in motion, or in other words, changes in segregation as they occur. Capturing changes in segregation as they occur will yield valuable information on where and how segregation or integration is taking place and among which ethnic and mover groups segregation or integration is occurring. LITERATURE REVIEW Residential Ethnic Segregation Residential ethnic segregation (segregation) is the degree to which various ethnic groups live in different neighborhoods (Iceland and Douzet 2006). Rates of segregation for blacks, Latinos, and Asians from the white population remain high. Of these groups, blacks experience

SEGREGATION IN MOTION 3 the most segregation (Wilkes and Iceland 2004). When segregation persists in an area, it can have serious negative social consequences on minority populations through the creation of an urban underclass, thus linking segregation to racial inequality (Massey 1993). In affected areas, residents have fewer economic and educational opportunities, thus limiting social mobility and residential choice. As residents remain in segregated areas, the place they call home is concentrated in poverty, physically deteriorated structures, higher rates of crime and mortality, and broken families (Massey 1993). It is important to study factors that influence levels of segregation in order to attempt to develop plans to overcome racial inequality. Research measuring change in segregation in metropolitan areas shows that even though rates of black segregation remain high, they are decreasing, revealing a slow move toward integration (Frey and Farley 1996). Integration of Latinos and Asians with the white population occurs more often than blacks. This trend is more likely to occur in multi-ethnic metropolitan areas where the population of other ethnic minority groups increases faster than blacks. Though, research shows trends towards convergence in levels of segregation when comparing different ethnic minority groups to the white population; black-white levels of segregation are decreasing while Latino-white and Asian-white levels are increasing (Frey and Farley 1996; Logan, Stults and Farley 2004). When measuring segregation among recent movers, we expect to find the same trends of integration because segregation trends occur through mobility. It is necessary to view theoretical perspectives to hypothesize about specific trends we would see when measuring residential ethnic segregation among different mover groups.

SEGREGATION IN MOTION 4 Theoretical Perspectives Theoretical perspectives have been applied to explain reasons for segregation. This section contains a brief discussion of the macro-sociological theory of social structure and the spatial assimilation theory, from which the delayed spatial assimilation theory, the immigrant enclave model, and the ethnic community models were derived. Blau (1977) developed the macro-sociological theory of social structure. This theory views social structure quantitatively as the distribution of a population existing in different social positions, with two main differentiations of heterogeneity and inequality. A component of this theory asserts that increasing heterogeneity promotes intergroup relations (Blau 1977: 52). This theorem, theorem nine, provides a basis for explaining the trends towards ethnic residential integration in a society with a nationally growing multi-ethnic population. The spatial assimilation theory was derived from the concept of spatial assimilation spatial distance implies social distance (Brown 2007). The theory posits that immigrant groups first settle in clusters near other co-ethnics because of reliance on them for social networks and support (Brown 2007). In the United States, assimilation and integration into the majority population occurs after learning the English language, which allows for economic advancement. Later generations of the initial immigrant groups are more assimilated with the majority population than incoming immigrant groups, and therefore experience less segregation from the majority population. The delayed spatial assimilation theory explains that in some cases, such as Mexican Americans, assimilation will occur in later generations because of hindrances to economic advancement like family ties (Brown 2007). When delayed assimilation occurs, segregation for some ethnic groups will remain high, showing slower rates of decline over time.

SEGREGATION IN MOTION 5 The formation of clustered immigrant groups upon arrival into the United States, when viewed through spatial assimilation theory, is explained by the immigrant enclave model (Logan, Zhang and Alba 2002). As stated earlier, these clusters or enclaves receive many new immigrant residents because of available social networks that can assist in assimilation. These newly arriving immigrants will be more segregated from the majority population when compared to immigrants that have begun the process of assimilation, the latter now moving towards more socially desirable neighborhoods among the native population. When the immigrants move out, segregation will decrease. In some cases, assimilated immigrants that have moved out of their original enclave begin to form their own ethnic community in suburbs or other more socially and economically desirable areas. This phenomenon describes the ethnic community model under the spatial assimilation theory (Logan, Zhang and Alba 2002). In this case, the assimilated immigrants chose to live with co-ethnics for reasons other than economic advancement such as personal preference or cultural identity. As the choice to move into ethnic communities is made, residents experience more segregation from members of other ethnic groups, including the majority population. Together with historical trends in segregation, these theoretical models were used to hypothesize segregation patterns among recent movers. Although much existing research measures the level of segregation at one point in time, these studies cannot speak to how segregation is changing. And whereas studies measuring segregation at several time points can provide information on the level of segregation at each time point, and how it therefore is changing, such studies are not able to say why these changes occur. We therefore adopt a novel approach that measures segregation among various recent mover groups to capture segregation patterns as they change.

SEGREGATION IN MOTION 6 RESEARCH QUESTION AND HYPOTHESES What does residential ethnic segregation among recent movers look like? This broad research question can be explored by dividing recent ethnic movers into different mover groups and comparing segregation rates amongst the groups and the static population. Segregation trends and theoretical findings can narrow this research question down through the testing of three hypotheses: hypothesis 1 (H1), the static population will be more segregated than domestic movers; hypothesis 2 (H2), long-distance movers will be more segregated than local movers from the static population; hypothesis 3 (H3), foreign movers will be more segregated than domestic movers. H1 states that segregation rates among the static population will be higher than segregation rates of different mover groups. More specifically, segregation rates of domestic movers of one ethnic group when compared to domestic movers of a different ethnic group will be less segregated than the static population of the first ethnic group when compared to the static population of the second ethnic group. Trends in segregation derived from measuring change of segregation rates over time show declines in segregation rates and integration of ethnic groups. We should observe this same effect when comparing segregation rates of different domestic mover groups to the static population. Furthermore, the theorem of macro-sociological structure explains increasing heterogeneity which leads to more intergroup relations. When comparing segregation rates among different ethnic recent movers to segregation rates of the static population, movers will have lower rates of segregation than the static population. H2, long-distance movers will be more segregated than local movers from the static population and H3, foreign movers will be more segregated than domestic movers can both be

SEGREGATION IN MOTION 7 explained by the spatial assimilation theory and the enclave model. When people move from further distances, they will likely first move into locations where co-ethnics are located. When this occurs as stated in H2, recent domestic movers from farther distances will be more segregated than recent domestic movers moving from shorter distances. Since foreign movers are coming from the farthest distances, this same reasoning can be applied to H3. METHODS A secondary data analysis was conducted using 2000 US Census Bureau SF 3 data on residence by race of the population five plus years old in 1995 at the state and county level for all 3,143 United States counties. This data source provided information for segregation comparisons between the static population and three groups of recent movers (in the last 5 years): same county movers (SCM), different county movers (DCM), and foreign movers (FM). For analysis of the hypotheses, domestic movers refer to same and different county movers together whereas all movers refer to same county, different county and foreign movers together. The index of dissimilarity was used to calculate segregation among recent movers. This index measures the proportion of one group under the condition of maximum segregation that would have to move in order to achieve evenness of the two groups in a geographic location (Massey 1988). It is calculated by taking the absolute value of the difference of the proportion of one group from the proportion of another group. It is then multiplied by one-half in order to truncate values between zero and one. Then, it is multiplied by 100 to express the rate of segregation as being between zero and 100. The following formula shows this calculation:

SEGREGATION IN MOTION 8 where A represents the total population of group A for the county, B represents the total population of group B for the county, a i is the total population of group A for the i th tract, and b i is the total population of group B for the i th tract. Segregation rates will range from zero to 100, zero representing complete integration of the two groups being measured and 100 representing complete segregation of the two groups being measured (Frey and Farley 1996). The dissimilarity index was calculated for 16 different mover group comparisons among three ethnic groups from 3,143 counties, yielding a total of 48 different dissimilarity indices (Appendix 1). Forty-eight mean dissimilarity indices were then calculated from the 3,143 counties to obtain a D value for each of the comparisons. In order to account for differences in population size across counties, the dissimilarity means were then weighted by population size using the following formula: In this formula, D n is the dissimilarity index for the n th county, P n is the population of the n th county, and P Total is the total population of all 3,143 counties. Weighted means of dissimilarity are interpreted as the rate of segregation experienced by the average group member that is being compared (Wilkes and Iceland 2004). RESULTS After calculating weighted mean dissimilarity values for the 48 dissimilarity indices of the 50 states, comparisons were made to determine segregation rates of recent ethnic movers. Hypothesis One H1 states that segregation rates among the static population will be higher than segregation rates of different mover groups. To test this hypothesis, the dissimilarity index for the static population of two ethnic groups was compared to the dissimilarity indices for domestic

SEGREGATION IN MOTION 9 movers of the same two ethnic groups. For example, D was calculated first for the white and black static populations and then was compared to D for both white and black same county movers (SCM) and white and black different county movers (DCM). This was done again for white-latino and black-latino comparisons of dissimilarity indices (Table 1). In table 1, results indicate that domestic movers are less segregated than the static population across all ethnic comparisons with the exception of Latino SCM to white SCM; this domestic mover group is more segregated than the white-latino static population. This can be interpreted as Latino SCM being more segregated than white SCM when compared to how segregated the Latino static population is from the white static population. This means that Latinos and whites are moving into different neighborhoods and where they are moving is causing them to be more segregated than the ethnic counterpart comparison of the static population. Other than the Latino-white SCM exception, domestic movers experience less segregation than the static population, confirming historical downward trends of segregation and theorem nine of Blau s macro-sociological theory of social structure. One explanation for this exception may be that Latinos moving within the same county are choosing to move into other Latino neighborhoods, possibly because of the existence of ethnic enclaves. Hypothesis Two Table 1. Indices of Dissimilarity for Comparison of Ethnic Static Populations to Domestic Mover Groups (H1) Stayers SCM DCM White-Black 59.5 57.5 52.0 White-Latino 45.3 48.8 43.1 Black-Latino 53.9 51.9 46.9 H2 states that long-distance movers will be more segregated than local movers from the static population. To test this, dissimilarity indices were calculated for one ethnic static

SEGREGATION IN MOTION 10 population to each of the mover groups of a different ethnic group. For example, dissimilarity was calculated for the white static population and black SCM, the white static population and black DCM, and the white static population and black foreign movers (FM). Then, dissimilarity indices were calculated between the same ethnic groups but in reverse order. For example, dissimilarity was calculated for the black static population and white SCM, the black static population and white DCM, and the black static population and white FM. The same framework of dissimilarity indices was calculated again for white-latino and black-latino comparisons (Table 2). Table 2. Indices of Dissimilarity for Comparison of Ethnic Static Populations to All Mover Groups (H2) White Stayers vs. White Stayers vs. Black Stayers vs. Black SCM 60.1 Latino SCM 51.2 Latino SCM 56.5 Black DCM 57.3 Latino DCM 46.9 Latino DCM 55.4 Black FM 70.9 Latino FM 64.8 Latino FM 64.0 Black Stayers vs. Latino Stayers vs. Latino Stayers vs. White SCM 58.9 White SCM 45.5 Black SCM 53.8 White DCM 60.2 White DCM 48.9 Black DCM 54.1 White FM 65.0 White FM 56.5 Black FM 64.8 In table 2, results indicate a trend that movers from greater distances experience more segregation from the static population than movers from shorter distances. Out of the 18 calculations of D for the comparisons that answer this hypothesis, there are three exceptions. Both black and Latino SCM are more segregated from the white static population than black and Latino DCM are from the white static population. Also, Latino SCM are more segregated from the black static population than Latino DCM. Other than these exceptions, H2 is maintained and confirms the spatial assimilation theory and ethnic enclave model. However, the exception in segregation rates from the white static population may confirm the delayed spatial assimilation theory for Latinos. It also confirms the persistence of high segregation rates for the black

SEGREGATION IN MOTION 11 population. Different county movers are a special mover group in that they are moving from the same country, just from farther distances. Social capital and economic status for different county movers may be higher than people moving around in the same county, allowing for lower rates of experienced segregation from the static population when moving in, as is seen in the results. Hypothesis Three H3 states that foreign movers will be more segregated than domestic movers. This hypothesis was tested using two main comparisons. The first test compares the D values for a domestic mover of one ethnicity compared to both a domestic mover of a second ethnicity and a foreign mover of that second ethnicity. When making this comparison, one of the domestic mover groups is held constant in each of the D calculations that were compared. For example, D for white SCM and black SCM (57.5) was compared to D for white SCM and black FM (69.4) (Table 3a). Table 3a. Indices of Dissimilarity for Comparison of Ethnic Domestic Mover Groups to Foreign Mover Groups (H3) White SCM vs. White SCM vs. Black SCM vs. Black SCM 57.5 Latino SCM 48.8 Latino SCM 57.5 Black FM 69.4 Latino FM 63.0 Latino FM 60.3 White DCM vs. White DCM vs. Black DCM vs. Black DCM 52.0 Latino DCM 43.1 Latino DCM 51.2 Black FM 67.5 Latino FM 63.7 Latino FM 60.6 Black SCM vs. Latino SCM vs. Latino SCM vs. White DCM 60.3 White DCM 53.0 Black DCM 60.0 White FM 63.3 White FM 57.8 Black FM 63.5 Black DCM vs. Latino DCM vs. Latino DCM vs. White SCM 54.6 White SCM 44.6 Black SCM 54.6 White FM 57.4 White FM 51.4 Black FM 61.3

SEGREGATION IN MOTION 12 A similar comparison was made using the opposite ethnic groups, as in hypothesis two, except now, D of black SCM and white DCM (60.3) was compared to D of black SCM and white FM (63.3) (Table 3a). Another comparison was made to test H3. Looking at Table 3b by column, a comparison was made between three different D values. One mover category for two different ethnicities was compared to the other two mover categories for the same two ethnicities. Table 3b. Indices of Dissimilarity for Comparison of Ethnic Domestic Mover Groups to Foreign Mover Groups (H3) White SCM vs. White SCM vs. Black SCM vs. Black SCM 57.5 Latino SCM 48.8 Latino SCM 57.5 White DCM vs. White DCM vs. Black DCM vs. Black DCM 52.0 Latino DCM 43.1 Latino DCM 51.2 White FM vs. White FM vs. Black FM vs. Black FM 65.4 Latino FM 63.6 Latino FM 62.9 For example, D for white-black SCM (57.5) was compared to D for white-black foreign movers (65.4). This was also done for white-black DCM (52.0) to white-black FM (65.4). This comparison was made for all ethnic group combinations. As we see from the example and examining tables 3a and b, hypothesis three was maintained for all comparisons. There is more segregation among groups of foreign movers than there is among groups of domestic movers. The spatial assimilation theory as applied to segregation among recent mover groups was confirmed. CONCLUSION In conclusion, segregation can be measured in motion when measuring ethnic residential segregation for different mover groups. We demonstrated the use of a novel technique in which

SEGREGATION IN MOTION 13 comparisons can be made to find out which ethnic mover groups are experiencing more or less segregation. Segregation among recent movers captures segregation as it is occurring through mobility and confirms changes in segregation that have been measured over time and theoretical explanations of segregation. This research design is an important contribution to the literature on segregation because it allows us to measure segregation as it is occurring. Findings reveal that domestic movers are almost always less segregated than the static population, that moving from farther distances almost always results in higher rates of segregation, and foreign movers are more segregated than other mover groups without exception. These findings are important for considerations of political action to help reduce inequality experienced today by the Latino population before they experience a similar situation as blacks did as described in the American Apartheid (Massey 1990). Future research suggestions for segregation among recent movers include using more recent data sets. Also, multivariate analysis is recommended to determine influences on rates of segregation for recent movers.

SEGREGATION IN MOTION 14 REFERENCES Alba, Richard D., John R. Logan, and Brian J. Stults. 2000. The Changing Neighborhood Contexts of the Immigrant Metropolis. Social Forces 79: 587-621 Blau, Peter. 1977. Inequality and Heterogeneity. 1st ed. New York: The Free Press. Brown, Susan K. 2007. Delayed Spatial Assimilation: Multigenerational Incorporation of the Mexican-Origin Population in Los Angeles. City & Community 6: 193-209. Charles, Camille Z., 2003. The Dynamics of Racial Residential Segregation. Annual Review of Sociology 29(1): 167-207. Frey, William H., Reynolds Farley. 1996. Latino, Asian, and Black Segregation in US Metropolitan Areas: Are Multiethnic Metros Different. Demography, 33(1): 35-50. Iceland J, Douzet F. 2006. Measuring Racial and Ethnic Segregation. Hérodote 122, 3: 25-43. Logan, John R., Stults, Brian J., and Farley, Reynolds. 2004. Segregation of Minorities in the Metropolis: Two Decades of Change. Demography, 41(1): 1-22. Logan, John R., Richard D. Alba, and Wenquan Zhang. 2002. Immigrant Enclaves and Ethnic Communities in New York and Los Angeles. American Sociological Review 67: 299-322. Maloutas, Thomas. 2004. Segregation and Residential Mobility: Spatially Entrapped Social Mobility And Its Impact on Segregation in Athens. European Urban and Regional Studies, 11(3): 195-211. Massey, Douglas S., and Nancy A. Denton. 1988. The Dimensions of Residential Segregation. Social Forces, 67(2): 281-315. Massey, Douglas. S., 1990. American Apartheid: Segregation and the Making of the Underclass. American Journal of Sociology, 96(2):329-357.

SEGREGATION IN MOTION 15 Massey, Douglas S., and Nancy A. Denton, 1993. American Apartheid: Segregation and the Making of the Underclass. Cambridge, Mass.: Harvard University Press. U.S. Census Bureau. Census 2000, Summary File 3. Generated by Victoria Pevarnik using Geolytics. http://demographics.geolytics.com/sf32000/preloginform.aspx. (23 November 2010). Wilkes, Rima, and John Iceland. 2004. Hypersegregation in the Twenty-First Century. Demography 41: 23-36.

SEGREGATION IN MOTION 16 APPENDIX Appendix. 48 calculations of the Index of Dissimilarity among recent ethnic mover groups White & Black Comparisons White & Latino Comparisons Black & Latino Comparisons Static Population White Stayers - Black Stayers White Stayers - Latino Stayers Black Stayers - Latino Stayers Static Population to All Mover Groups White Stayers - Black SCM White Stayers - Latino SCM Black Stayers - Latino SCM White Stayers - Black DCM White Stayers - Latino DCM Black Stayers - Latino DCM White Stayers - Black FM White Stayers - Latino FM Black Stayers - Latino FM Black Stayers - White SCM Latino Stayers - White SCM Latino Stayers - Black SCM Black Stayers - White DCM Latino Stayers - White DCM Latino Stayers - Black DCM Black Stayers - White FM Latino Stayers - White FM Latino Stayers - Black FM Domestic Movers White SCM - Black SCM White SCM - Latino SCM Black SCM - Latino SCM White SCM - Black DCM White SCM - Latino DCM Black SCM - Latino DCM White DCM - Black SCM White DCM - Latino SCM Black DCM - Latino SCM White DCM - Black DCM White DCM - Latino DCM Black DCM - Latino DCM Foreign Movers to Domestic Movers White FM - Black SCM White FM - Latino SCM Black FM - Latino SCM White FM - Black DCM White FM - Latino DCM Black FM - Latino DCM Black FM - White SCM Latino FM - White SCM Latino FM - Black SCM Black FM - White DCM Latino FM - White DCM Latino FM - Black DCM

SEGREGATION IN MOTION 17 TABLES Table 1. Indices of Dissimilarity for Comparison of Ethnic Static Populations to Domesitc Mover Groups (H1) Stayers SCM DCM White-Black 63.9 61.0 55.2 White-Latino 47.8 48.2 43.5 Black-Latino 53.8 50.7 45.6 Table 2. Indices of Dissimilarity for Compairson of Ethnic Static Populations to All Mover Groups (H2) White Stayers vs. White Stayers vs. Black Stayers vs. Black SCM 63.5 Latino SCM 50.2 Latino SCM 55.1 Black DCM 60.5 Latino DCM 46.5 Latino DCM 56.0 Black FM 75.6 Latino FM 63.5 Latino FM 63.1 Black Stayers vs. Latino Stayers vs. Latino Stayers vs. White SCM 63.3 White SCM 48.6 Black SCM 54.1 White DCM 65.1 White DCM 53.2 Black DCM 55.0 White FM 69.6 White FM 60.0 Black FM 69.2 Table 3a. Indices of Dissimilarity for Comparison of Ethnic Domestic Mover Groups to Foreign Mover Groups (H3) White SCM vs. White SCM vs. Black SCM vs. Black SCM 57.5 Latino SCM 48.8 Latino SCM 57.5 Black FM 69.4 Latino FM 63.0 Latino FM 60.3 White DCM vs. White DCM vs. Black DCM vs. Black DCM 52.0 Latino DCM 43.1 Latino DCM 51.2 Black FM 67.5 Latino FM 63.7 Latino FM 60.6 Black SCM vs. Latino SCM vs. Latino SCM vs. White DCM 60.3 White DCM 53.0 Black DCM 60.0 White FM 63.3 White FM 57.8 Black FM 63.5 Black DCM vs. Latino DCM vs. Latino DCM vs. White SCM 54.6 White SCM 44.6 Black SCM 54.6 White FM 57.4 White FM 51.4 Black FM 61.3

SEGREGATION IN MOTION 18 TABLES (continued) Table 3b. Indices of Dissimilarity for Comparison of Ethnic Domestic Mover Groups to Foreign Mover Groups (H3) White SCM vs. White SCM vs. Black SCM vs. Black SCM 57.5 Latino SCM 48.8 Latino SCM 57.5 White DCM vs. White DCM vs. Black DCM vs. Black DCM 52.0 Latino DCM 43.1 Latino DCM 51.2 White FM vs. White FM vs. Black FM vs. Black FM 65.4 Latino FM 63.6 Latino FM 62.9